title: Effect of promoter architecture on the cell-to-cell variability in gene expression.
abstract: According to recent experimental evidence, promoter architecture, defined by the number, strength and regulatory role of the operators that control transcription, plays a major role in determining the level of cell-to-cell variability in gene expression. These quantitative experiments call for a corresponding modeling effort that addresses the question of how changes in promoter architecture affect variability in gene expression in a systematic rather than case-by-case fashion. In this article we make such a systematic investigation, based on a microscopic model of gene regulation that incorporates stochastic effects. In particular, we show how operator strength and operator multiplicity affect this variability. We examine different modes of transcription factor binding to complex promoters (cooperative, independent, simultaneous) and how each of these affects the level of variability in transcriptional output from cell-to-cell. We propose that direct comparison between in vivo single-cell experiments and theoretical predictions for the moments of the probability distribution of mRNA number per cell can be used to test kinetic models of gene regulation. The emphasis of the discussion is on prokaryotic gene regulation, but our analysis can be extended to eukaryotic cells as well.
authors.affiliation: Graduate Program in Biophysics and Structural Biology, Brandeis University, Waltham, Massachusetts,USA.
authors.forename: Alvaro
authors.initials: A
authors.lastname: Sanchez
authors.forename: Hernan G
authors.initials: HG
authors.lastname: Garcia
authors.forename: Daniel
authors.initials: D
authors.lastname: Jones
authors.forename: Rob
authors.initials: R
authors.lastname: Phillips
authors.forename: Jané
authors.initials: J
authors.lastname: Kondev
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D019295:Computational Biology; D004926:Escherichia coli / Q000235:genetics; D015964:Gene Expression Regulation, Bacterial; D007700:Kinetics; D008957:Models, Genetic; D056004:Molecular Dynamics Simulation; D016012:Poisson Distribution; D011401:Promoter Regions, Genetic; D012097:Repressor Proteins; D013269:Stochastic Processes
chemical_list: D012097:Repressor Proteins